Living England is a multi-year project which delivers a broad habitat map for the whole of England, created using satellite imagery, field data records and other geospatial data in a machine learning framework. The Living England habitat map shows the extent and distribution of broad habitats across England aligned to the UKBAP classification, providing a valuable insight into our natural capital assets and helping to inform land management decisions. Living England is a project within Natural England, funded by and supports the Defra Natural Capital and Ecosystem Assessment (NCEA) Programme and Environmental Land Management (ELM) Schemes to provide an openly available national map of broad habitats across England.This dataset includes very complex geometry with a large number of features so it has a default viewing distance set to 1:80,000 (City in the map viewer).Process Description:A number of data layers are used to develop a ground dataset of habitat reference data, which are then used to inform a machine-learning model and spatial analyses to generate a map of the likely locations and distributions of habitats across England. The main source data layers underpinning the spatial framework and models are Sentinel-2 and Sentinel-1 satellite data from the ESA Copernicus programme, Lidar from the EA's national Lidar Programme and collected data through the project's national survey programme. Additional datasets informing the approach as detailed below and outlined in the accompanying technical user guide.Datasets used:OS MasterMap® Topography Layer; Geology aka BGS Bedrock Mapping 1:50k; Long Term Monitoring Network; Uplands Inventory; Coastal Dune Geomatics Mapping Ground Truthing; Crop Map of England (RPA) CROME; Lowland Heathland Survey; National Grassland Survey; National Plant Monitoring Scheme; NE field Unit Surveys; Northumberland Border Mires Survey; Sentinel-2 multispectral imagery; Sentinel-1 backscatter imagery; Sentinel-1 single look complex (SLC) imagery; National forest inventory (NFI); Cranfield NATMAP; Agri-Environment HLS Monitoring; Living England desktop validation; Priority Habitat Inventory; Space2 Eye Lens: Ainsdale NNR, State of the Bog Bowland Survey, State of the Bog Dark Peak Condition Survey, State of the Bog Manchester Metropolitan University (MMU) Mountain Hare Habitat Survey Dark Peak, State of the Bog; Moors for the Future Dark Peak Survey; West Pennines Designation NVC Survey; Wetland Annex 1 inventory; Soils-BGS Soil Parent Material; Met Office HadUK gridded climate product; Saltmarsh Extent and Zonation; EA LiDAR DSM & DTM; New Forest Mires Wetland Survey; New Forest Mires Wetland Survey; West Cumbria Mires Survey; England Peat Map Vegetation Surveys; NE protected sites monitoring; ERA5; OS Open Built-up Areas; OS Boundaries dataset; EA IHM (Integrated height model) DTM; OS VectorMap District; EA Coastal Flood Boundary: Extreme Sea Levels; AIMS Spatial Sea Defences; LIDAR Sand Dunes 2022; EA Coastal saltmarsh species surveys; Aerial Photography GB (APGB); NASA SRT (Shuttle Radar Topography Mission) M30; Provisional Agricultural Land Classification; Renewable Energy Planning Database (REPD); Open Street Map 2024.Attribute descriptions: Column Heading Full Name Format Description

SegID SegID Character (100) Unique Living England segment identifier. Format is LEZZZZ_BGZXX_YYYYYYY where Z = release year (2223 for this version), X = BGZ and Y = Unique 7-digit number

Prmry_H Primary_Habitat Date Primary Living England Habitat

Relblty Reliability
Character (12) Reliability Metric Score

Mdl_Hbs Model_Habs Interger List of likely habitats output by the Random Forest model.

Mdl_Prb Model_Probs Double (6,2) List of probabilities for habitats listed in ‘Model_Habs’, calculated by the Random Forest model.

Mixd_Sg Mixed_Segment Character (50) Indication of the likelihood a segment contains a mixture of dominant habitats. Either Unlikely or Probable.

Source Source

Description of how the habitat classification was derived. Options are: Random Forest; Vector OSMM Urban; Vector Classified OS Water; Vector EA saltmarsh; LE saltmarsh & QA; Vector RPA Crome, ALC grades 1-4; Vector LE Bare Ground Analysis; LE QA Adjusted

SorcRsn Source_Reason

Reasoning for habitat class adjustment if ‘Source’ equals ‘LE QA Adjusted’

Shap_Ar Shape_Area

Segment area (m2) Full metadata can be viewed on data.gov.uk.

The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.

The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable.

Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes.

Datasets used: Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate Data

PLEASE NOTE: This data product is not available in Shapefile format or KML at https://naturalengland-defra.opendata.arcgis.com/datasets/Defra::living-england-habitat-map-phase-4/about, as the data exceeds the limits of these formats. Please select an alternative download format.This data product is also available for download in multiple formats via the Defra Data Services Platform at https://environment.data.gov.uk/explore/4aa716ce-f6af-454c-8ba2-833ebc1bde96?download=true.The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used:Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate DataFull metadata can be viewed on data.gov.uk.

Spatial datasets consider the lands contribution to preventing and mitigating climate change, through storage of carbon in the Soils (below ground). This below Ground Carbon spatial datasets represent a strategic resource for England, that indicate the range of carbon storage values in tonnes of carbon per hectare (t C Ha-1 ). At a local scale (e.g. 1:50 000). They are presented as a series of raster datasets for use in GIS Systems at a resolution of 25m2. These maps will assist users to find out where the most important carbon stores in soils in their areas. They are not suitable for field scale carbon mitigation as this would require field scale carbon assessment. As well as soil being an excellent natural carbon sink, locking carbon away from the atmosphere and reducing the amount of greenhouse gasses produced soil carbon has a number of other excellent benefits. The amount of carbon stored within mineral soil depends upon the soil type, with clay rich and silt rich soils storing more carbon than sandy soils. Within peat soils, carbon storage operates by a different process. In a non-compromised or fully functional state peat soils are fully saturated with water for most of the year. This leads to the minimal decomposition of plant biomass, so soil carbon builds up faster than decomposition can occur, so no equilibrium is reached, to form a very carbon-rich layer of peat. However, if the peats are damaged so leading to drying out the soil microbial activity can re-start, and as the carbon is utilised by the soil microfauna, carbon dioxide and methane are then released to the atmosphere, changing a carbon sink that is sequestering carbon, into a source of greenhouse gas emissions. (UK Peatland Strategy 2018) . Natural England produced a report in 2021 reviewing this research and compiling different land use. approximate values in tons per hectare of carbon for a wide variety of habitats in England (Gregg et al 2021) see Carbon Storage and Sequestration by Habitat 2021 (NERR094). Framework created from Soilscapes and NE Natural England Peat Map (Natural England 2008).Soilscapes- 1:250,000 scale soils dataset. [https://www.landis.org.uk/soilsguide/soilscapes_list.cfm ]. the 27 soils carbon figure was assigned. This data was split in 2; Mineral Soils; Organo mineral & Peat Soils. Mineral soil split by habitats. modified by: PHI habitat overlying the soil (more natural / semi-natural the higher the score) with 50% overlap = 30% uplift carbon; the Ancient Woodland (NE 2019) with 50% overlap add 30% uplift in carbon. Organo Mineral & Peat soils: NE Peat Map (2008) was used to describe the shallow and deep peat soils, inc. peaty pockets. then conflated with the Soilscape for organo -mineral soils and peat soils with the NE peat map having priority. Modifiers were used & included: Indications that the habitats might be in good ecological condition, the PHI and the SSSI was used as a proxy. If no PHI overlap a 10% reduction; If the habitat overlying the soil is Fen = 2 x carbon figure. If the habitat overlying the soil is Raised Bog = 2.5 x carbon figure; Arable = reduced carbon lost from peat soils under. The Mineral and Organo mineral & Peat Soils re-joined to single England layer. Then Soil depth & Slope adjustment. Soil depth important to carbon stored. Most carbon in the topsoil, lesser amount of carbon held deep in soil profiles. Put into the model each soil type was allocated to one of four depth classes: Shallow soils with a profile likely to be 15-50 cm or less; The models assumed a 30 cm depth for carbon calculations; Normal depth mineral soils with a profile between 1 m and 1.25 m. The models assumed a 1 m depth for carbon calculations. Blanket peat soils. The models assumed a 2 m depth for carbon calculations. Raised bog and fen peat soils. Model assumed 4 m depth for carbon calculations. Slope, habitats occurring on steep slopes have thinner soil. A value of over 18o was used to show as a proxy for thinner soils. Slope occurring on; on slopes between 0-11o = 0%; on slopes between 11o - 18o = -10%; on slopes over 18o = -20%. NE PHI/ Ancient Woodland - OGL NE Living England - OGL NE Peat Map [2008] - Non- commercial licence Soilscapes - Cranfield University- NE Bespoke Licence SRTM- NASA Shuttle Radar Topography- Open Topography Attribution statement: © Natural England [Year], reproduced with the permission of Natural England, www.gov.uk/natural-england. © Crown Copyright and database right [Year]. Ordnance Survey licence number AC0000851168. Contains, or is based on, information supplied by the Forestry Commission. © Crown copyright and database right [Year] Ordnance Survey 100021242 Soils Data © Cranfield University (NSRI) and for the Controller of HMSO [Year] Need to add text for SRTM NASA Shuttle Radar Topography Mission (SRTM)(2013). Shuttle Radar Topography Mission (SRTM) Global. Distributed by OpenTopography. https://doi.org/10.5069/G9445JDF. Accessed: 2024-05-17

This is a spatial dataset which defines the regions for the Living England Phase IV habitat classification. 14 regions were created in England to balance resource requirements and scalability. The regions are based on National Character Areas which are grouped such that each region is covered by a single European Space Agency Sentinel-2 satellite orbit (with the exception of Zone 10 in the SE which is covered by two orbits), and such that the regions are approximately similar in size.

The Access Network Map of England is a national composite dataset of Access layers, showing analysis of extent of Access provision for each Lower Super Output Area (LSOA), as a percentage or area coverage of access in England. The ‘Access Network Map’ was developed by Natural England to inform its work to improve opportunities for people to enjoy the natural environment. This map shows, across England, the relative abundance of accessible land in relation to where people live. Due to issues explained below, the map does not, and cannot, provide a definitive statement of where intervention is necessary. Rather, it should be used to identify areas of interest which require further exploration. Natural England believes that places where people can enjoy the natural environment should be improved and created where they are most wanted. Access Network Maps help support this work by providing means to assess the amount of accessible land available in relation to where people live. They combine all the available good quality data on access provision into a single dataset and relate this to population. This provides a common foundation for regional and national teams to use when targeting resources to improve public access to greenspace, or projects that rely on this resource. The Access Network Maps are compiled from the datasets available to Natural England which contain robust, nationally consistent data on land and routes that are normally available to the public and are free of charge. Datasets contained in the aggregated data:•
Agri-environment scheme permissive access (routes and open access)•
CROW access land (including registered common land and Section 16)•
Country Parks•
Cycleways (Sustrans Routes) including Local/Regional/National and Link Routes•
Doorstep Greens•
Local Nature Reserves•
Millennium Greens•
National Nature Reserves (accessible sites only)•
National Trails•
Public Rights of Way•
Forestry Commission ‘Woods for People’ data•
Village Greens – point data only Due to the quantity and complexity of data used, it is not possible to display clearly on a single map the precise boundary of accessible land for all areas. We therefore selected a unit which would be clearly visible at a variety of scales and calculated the total area (in hectares) of accessible land in each. The units we selected are ‘Lower Super Output Areas’ (LSOAs), which represent where approximately 1,500 people live based on postcode. To calculate the total area of accessible land for each we gave the linear routes a notional width of 3 metres so they could be measured in hectares. We then combined together all the datasets and calculated the total hectares of accessible land in each LSOA. For further information about this data see the following links:Access Network Mapping GuidanceAccess Network Mapping Metadata Full metadata can be viewed on data.gov.uk.

Areas of Outstanding Natural Beauty (AONBs) are designated areas where protection is afforded to protect and manage the areas for visitors and local residents. AONBs are also known as National Landscapes.Under the Countryside and Rights of Way Act 2000, Natural England has the power to designate AONBs in England that are outside national parks and that are considered to have such natural beauty it is desirable they are conserved and enhanced; issue a variation order to change an existing AONB boundary. It also holds a duty to give advice on developments taking place in an AONB; take into account the conservation and enhancement of AONBs in its work.National Landscapes are living places. Area of Outstanding Natural Beauty is not a nature designation, and caring for the natural beauty of these places involves more than habitat restoration.There are 46 National Landscapes in the UK. These are places with national importance, protected for the nation's benefit, but cared for by local teams with a deep understanding of the distinctive web of interconnecting factors that make these places special.The physical geography in a National Landscape: the unique combination of landform, climate and geology determines which species thrive, which industries grow, and therefore the heritage, language and culture of the individual place.For more information visit https://national-landscapes.org.uk/.Full metadata can be viewed on data.gov.uk.

Projekt Living England, prowadzony przez Natural England, jest wieloletnim programem zapewniającym pochodzącą z satelity krajową warstwę siedliskową w celu wsparcia systemu zarządzania gruntami środowiskowymi (ELM) oraz pilotażowego programu oceny kapitału naturalnego i ekosystemów (NCEA). W projekcie zastosowano podejście oparte na uczeniu maszynowym do klasyfikacji obrazów, opracowane w ramach projektu Defra Living Maps (SD1705 – Kilcoyne i in., 2017). Metoda najpierw grupuje jednorodne obszary siedlisk w segmenty, a następnie przypisuje każdy segment do określonej listy klas siedlisk za pomocą losowego lasu (algorytm uczenia maszynowego). Mapa prawdopodobieństwa siedlisk przedstawia modelowane prawdopodobnie ogólne klasyfikacje siedlisk, przeszkolone w zakresie badań terenowych i danych z obserwacji Ziemi z 2021 r., a także warstw danych historycznych. Mapa ta jest wynikiem etapu IV projektu Living England, a przyszłe prace w ramach etapu V (2022–23) mają na celu ujednolicenie metodyki, a etap VI (2023–24) – wdrożenie uzgodnionych znormalizowanych metod.

Mapa prawdopodobieństwa siedliska Living England dostarczy dokładnych, spójnych przestrzennie danych dla szeregu potrzeb w zakresie realizacji polityki Defra (np. wskaźniki 25YEP i sprawozdawczość na temat celów ustawy o środowisku Natural Capital Accounting, Nature Strategy, ELM), a także użytkowników zewnętrznych. Jako mapa prawdopodobieństwa umożliwia ekstrapolację danych na obszary, w których nie mamy danych. Dane te będą również wspierać lepsze podejmowanie decyzji na szczeblu lokalnym i krajowym, rozwój polityki i ocenę, zwłaszcza w obszarach, w których inne formy dowodów są niedostępne.

Opis procesu: Szereg warstw danych są wykorzystywane do informowania modelu w celu zapewnienia mapy prawdopodobieństwa siedliska Anglii. Głównymi warstwami źródłowymi są dane satelitarne z satelitów Sentinel-2 i Sentinel-1 z programu ESA Copericus. Do modelu włączono dodatkowe zbiory danych (jak wyszczególniono poniżej), aby ułatwić segmentację i klasyfikację określonych klas siedlisk.

Wykorzystane zbiory danych: Monitorowanie zarządzania na wyższym poziomie w rolnictwie i środowisku (HLS), British Geological Survey Bedrock Mapping 1:50k, Geomatyka wydm przybrzeżnych Mapowanie terenu, Mapa upraw Anglii (RPA), Badanie stanu torfowisk Dark Peak, Walidacja pulpitu i punkty ręczne, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Jednostka terenowa NEFU, Living England Collector App NEFU/EES, Sieć długoterminowego monitorowania (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District, Priority Habitats Inventory (PHI) B Button, Europejska Agencja Kosmiczna (ESA) Sentinel-1 i Sentinel-2, Space2 Eye Lens: Ainsdale NNR, soczewka oczna Space2: State of the Bog Bowland Survey, Space2 Eye Lens (ang.). State of the Bog Dark Peak Condition Survey, Space2 Eye Lens (ang.). State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim – Global Climate Data Attribution Statement [Oświadczenie o przypisaniu globalnych danych klimatycznych]: „Zawiera dane dostarczone przez ©Natural England ©Centre for Ecology and Hydrology, Natural England Licence No. 2011/052 British Geological Survey © NERC. Wszelkie prawa zastrzeżone., © Prawo autorskie Agencji Środowiska i/lub prawo do bazy danych 2015. Wszelkie prawa zastrzeżone. ©Natural England © Crown copyright and database right [2014], © Rural Payments Agency, © Natural England © 1995–2020 Esri, Zawiera informacje Agencji Środowiska © Environment Agency i/lub prawa do baz danych. Niektóre informacje użyte w tym produkcie to © Bluesky International Ltd / Getmapping PLC. Zawiera ogólnodostępne dane dostarczone przez Natural Environment Research Council (Centrum Ekologii i Hydrologii; British Antarctic Survey (brytyjski przegląd antarktyczny); British Geological Survey (ang.). Zawiera dane OS © Crown copyright and database right, © Environment Agency copyright and/or database right 2015. Wszelkie prawa zastrzeżone., Esri, Maxar, Earthstar Geographics, USDA FSA, USGS, Aerogrid, IGN, IGP i społeczność użytkowników GIS, Zawiera dane Ordnance Survey © Crown copyright and database right 2021., EODS / CEDA ARD: ESA Copernicus: „Zawiera zmodyfikowane dane z satelitów Sentinel programu Copernicus [2021]”, © Carlos Bedson Manchester Metropolitan University, © Copyright 2020, worldclim.org”

Fick, S.E. i R.J. Hijmans, 2017. WorldClim 2 (ang.) nowe powierzchnie klimatyczne o rozdzielczości przestrzennej 1 km dla globalnych obszarów lądowych. International Journal of Climatology (Międzynarodowy Dziennik Klimatologiczny) 37 (12): 4302-4315.

Pescott, O.L.; Walker, K.J.; Dzień, J.; Harris, F.; Roy, D.B. (2020). Dane z badań w ramach krajowego systemu monitorowania roślin (2015–2019). NERC Environmental

This layer identifies some of the strategic opportunities in your area for positive change and work out plans with land managers to enhance carbon, whatever the current land use. It will help you understand whether you are aiming to increase carbon by a smaller amount over a large area or concentrate on a couple of smaller schemes where there will be a large enhancement such as tree planting on low intensity (species poor) grassland. In this layer we have followed the IPCC methodology for reporting carbon emissions . Emissions are recorded as a positive value as they are adding to the carbon burden in the atmosphere. Sequestration is recorded as a negative value as it is removing carbon from the atmosphere. Carbon sequestration maps shows where the environment is actively capturing carbon dioxide and binding it in plants and soils. What is being captured now with the current land use, habitats and crops. As sequestration is much more dependent on land use and management practices which vary more widely this data is only a guide for broad trends not local differences in management. i.e. where woodland or grassland cover is consistent not variation between farming practices in fields or woodland management at a local area. It is measured as tonnes of carbon dioxide equivalent per hectare per year (t CO2e ha-1 y-1 ).Many areas in agricultural production will have a neutral carbon balance where land management is sufficient to replace carbon lost in cropping or grazing from the vegetation and tillage from the soil. However, some soil types are very vulnerable to losing carbon when actively managed, these includes the very fertile but deep lowland agricultural peats. The figures for habitat sequestration of carbon are taken from the Natural England Report NERR094 (Gregg et.al. 2021). This report identified some key gaps. Each habitat type was assigned a likely score for sequestration. Carbon sequestration is less researched and harder to measure and therefore the confidence in this dataset is lower than in the carbon storage dataset.

Three data component layers were collated together to form a continuous habitat data layer for England: The National Forest Inventory (2016); NE priority habitat Inventory (PHI) dataset (various dated); Living England habitat map from satellite imagery (2020). Each of the habitats was assigned a likely sequestration value. Management influences sequestration, additional data sets adjust the figures and hence outputs spatially this included: - the protected site data given a slight uplift to the scores; - woodland sites on very steep slopes a slight reduction was given; - if mineral soils had native vegetation designated by the PHI, values were slightly uplifted; - soil type is important to sequestration with peatland soils losing carbon under arable and intensive grasslands at an extremely fast rate. - The peatland maps were combined with the vegetation maps to highlight these areas. Management of soil in intensive pastoral and arable peat systems has a profound effect on soil carbon values. - It is easy to lose carbon repeatedly from a system due to ploughing. For this report we have therefore assumed that these productive systems have a neutral carbon sequestration result. This is an over simplification and for more detailed studies information about the types of management regimes and more detailed soil information would be needed to understand if these areas are a carbon source or sink. NE PHI/ Ancient Woodland - OGL NE Living England - OGL NE Peat Map [2008] - Non- commercial licence NE SSSI data NFI-National Forest Inventory (NFI) Forest Research- OGL Soilscapes - Cranfield University/ HMSO- NE Bespoke Licence SRTM- NASA Shuttle Radar Topography- Open Topography

These spatial datasets consider the lands contribution to preventing and mitigating climate change, through storage of carbon in the Soils (below ground) & Vegetation (above ground). This total carbon spatial datasets represent a strategic resource for England, that indicate the range of carbon storage values in tonnes of carbon per hectare (t C Ha-1 ). At a local scale (e.g. 1:50 000). They are presented as a series of raster datasets for use in GIS Systems at a resolution of 25m2. These maps will assist users to find out where the most important carbon stores in soils in their areas. They are not suitable for field scale carbon mitigation as this would require field scale carbon assessment. It is often the case that where we have lower below ground carbon (mineral soils) the conditions are great for better tree and vegetation growth to get greater above ground carbon storage. Where below ground carbon storage is greater this is due to wetter conditions and soil waterlogging reducing organic matter decomposition. This leads to poorer growing conditions that result in lower above ground carbon storage. The addition of the above and below ground carbon layers seems to mean that carbon data is more homogenised and has much less carbon variation within areas. Although Total Carbon Storage is useful the data user will also need to refer back to input data to understand why the results occur across the landscape area.

Total Carbon Storage adds the two carbon storage layers together. As the above & below ground carbon storage layers indicate the range of carbon storage values in tonnes of carbon per hectare (t C Ha-1 ). At a local scale (e.g. 1:50 000). They are presented as a series of raster datasets for use in GIS Systems at a resolution of 25m2. Each 25m2 has a carbon total form the layers and these are added together spatially to create the total carbon layer in tonnes of carbon per hectare (t C Ha-1 ) NE PHI/ Ancient Woodland - OGL NE Living England - OGL NE Peat Map [2008] - Non- commercial licence NFI-National Forest Inventory (NFI) Forest Research- OGL Soilscapes - Cranfield University- NE Bespoke Licence SRTM- NASA Shuttle Radar Topography- Open Topography

The survey of the marine environment of Falmouth Bay and the lower Fal Ruan Estuary was undertaken as part of the BioMar Project which is funded by the European Community through the LIFE Programme. In July 1994 a baseline survey was done to map the distribution of dead and living maerl. The survey was done using a RoxAnn acoustic system supported by direct observation of the seabed using a drop-down video camera and sediment samples collected by grab. Maps of bathymetry and predicted distribution of biotopes were prepared using GIS.

These spatial datasets consider the lands contribution to preventing and mitigating climate change, through storage of carbon in the Soils (below ground) & Vegetation (above ground). This total carbon spatial datasets represent a strategic resource for England, that indicate the range of carbon storage values in tonnes of carbon per hectare (t C Ha-1 ). At a local scale (e.g. 1:50 000). They are presented as a series of raster datasets for use in GIS Systems at a resolution of 25m2. These maps will assist users to find out where the most important carbon stores in soils in their areas. They are not suitable for field scale carbon mitigation as this would require field scale carbon assessment. It is often the case that where we have lower below ground carbon (mineral soils) the conditions are great for better tree and vegetation growth to get greater above ground carbon storage. Where below ground carbon storage is greater this is due to wetter conditions and soil waterlogging reducing organic matter decomposition. This leads to poorer growing conditions that result in lower above ground carbon storage. The addition of the above and below ground carbon layers seems to mean that carbon data is more homogenised and has much less carbon variation within areas. Although Total Carbon Storage is useful the data user will also need to refer back to input data to understand why the results occur across the landscape area. Total Carbon Storage adds the two carbon storage layers together. As the above & below ground carbon storage layers indicate the range of carbon storage values in tonnes of carbon per hectare (t C Ha-1 ). At a local scale (e.g. 1:50 000). They are presented as a series of raster datasets for use in GIS Systems at a resolution of 25m2. Each 25m2 has a carbon total form the layers and these are added together spatially to create the total carbon layer in tonnes of carbon per hectare (t C Ha-1 ) NE PHI/ Ancient Woodland - OGL NE Living England - OGL NE Peat Map [2008] - Non- commercial licence NFI-National Forest Inventory (NFI) Forest Research- OGL Soilscapes - Cranfield University- NE Bespoke Licence SRTM- NASA Shuttle Radar Topography- Open Topography Attribution statement: © Natural England [Year], reproduced with the permission of Natural England, www.gov.uk/natural-england. © Crown Copyright and database right [Year]. Ordnance Survey licence number AC0000851168. Contains, or is based on, information supplied by the Forestry Commission. © Crown copyright and database right [Year] Ordnance Survey 100021242 Soils Data © Cranfield University (NSRI) and for the Controller of HMSO [Year] NASA Shuttle Radar Topography Mission (SRTM)(2013). Shuttle Radar Topography Mission (SRTM) Global. Distributed by OpenTopography. https://doi.org/10.5069/G9445JDF. Accessed: 2024-05-17

This dataset defines the boundaries of twelve Nature Recovery Projects forming a key part of the 25 Year Environment Plan’s commitment to deliver the Nature Recovery Network (NRN). The twelve projects included in this dataset are: East of Eden, Purple Horizons, Somerset Coast Levels and Moors, G7 Legacy, Wye Valley, Wendling Beck, Lost Wetlands, Heathland Connections, Bradford & South Pennines, Seaford to Eastbourne: Drink-in the Downs, Tees Estuary Recovering Nature (TERN), Cambridge Nature Network. The boundary for the Lost Wetlands Project has not yet been confirmed and is subject to change.The Nature Recovery Projects form a key part of the 25 Year Environment Plan’s commitment to deliver the Nature Recovery Network (NRN). They aim to follow Lawton principles to create more, bigger, better and, crucially, connected, sustained and functional wildlife-rich places. Places that counter biodiversity loss, adapt to climate change and support the needs of local communities. They will provide natural solutions to reduce carbon emissions, enhance our landscapes and cultural heritage, manage flood risk and enable  people to enjoy and connect with nature where they live, work and play – benefiting health and wellbeing. This dataset shows the location and boundaries of Nature Recovery Projects throughout England. The main outline of each one was provided by the project lead, and in some cases these were refined by following geographic or administrative boundairies as listed below: OS Open rivers (OGL), AONBs (OGL), County Boundaries (OGL), OS Open Roads (OGL), SSSIs (OGL), Environmentally Sensitive Areas (OGL), Flood Risk Zone 3 (OGL), NNRs (OGL), Marine Conservation Zone (OGL).Full metadata can be viewed on data.gov.uk.